The energy and its entire related infrastructure are the main drivers for a economic development and for ensuring a good level of employment. As part of a global study about international energy sector, we evaluate here the impact of technological changes on the state of the energy infrastructure. This study includes a detailed analysis of the global challenges facing the energy industry. We propose scenarios for the development of a modernized energy infrastructure with an assessment of the entire energy system. Our evaluation indicators are chosen in terms of the reliability of the energy infrastructure, of its quality, of the accidents that may happen and of the consequent environmental risks. This study is particularly adapted for forecasting the necessary measures (of technical nature, of governance kind) that have to be implemented to reduce the acceleration of the infrastructure deterioration rate. Our results reveal that the use of digital and information technologies has many positive impacts on the development and on the control of an efficient consumption of energy. In addition, our predictions, due to the further modernization of the energy sector, can contribute and help in the creation of preconditions that will be highly stimulating and profitable to the growth of investments in the energy infrastructure.

There is a tendency to increase the use of demand response technology in the Russian Federation along with other developing countries, covering not only large industries, but also individual households and organizations. Reducing peak loads of electricity consumption and increasing energy efficient use of equipment in the power system is achieved by applying demand management technology based on modeling and predicting consumer behavior in an educational institution. The study proposes to consider the possibility of participating in the concept of demand management of educational institutions with a typical workload schedule of the work week. For the study, statistical data of open services and sources, Russian and foreign research on the use of digital and information technologies, analytical methods, methods of mathematical modeling, methods of analysis, and generalization of data and statistical methods of data processing are used. An algorithm for collecting and processing power consumption data and a load planning algorithm were developed, including all levels of interaction between devices. A comparison was made between the values of the maximum daily consumption before and after optimization, as well as the magnitude of the decrease in the maximum consumption after applying the genetic algorithm. The developed algorithm has the ability to scale, which will increase the effect of using the results of this study to more significant values. Load switching helps to reduce peak consumption charges, which often represent a significant portion of the electricity cost.

Dramatic changes in the global energy market due to COVID-19 pandemic, the OPEC+ agreement, and increasing rates of green energy share in the world community have brought nega-tive effects on the oil sector. In the long term, oil will reduce its importance as an energy resource, but for many years, it will continue to play a significant role in the world of energy. The oil industry has huge potential in terms of technical expertise, management, and financial resources to reduce its greenhouse emissions and ensuring an affordable availability of predictable energy. However, nowadays this sector has lost investing attractiveness. It is an interdisciplinary problem with a so-lution at the intersection of different stakeholders’ interests. The article is a review one and devoted to the issue of the implementation a public-private partnership (PPP) as a key tool that allows the use of the state and the business’ available resources to achieve the sector’s sustainable development and investment attractiveness. Research and analysis of PPP were based on foreign and domestic literature, using classification and generalization methods, retrospective and critical analysis. This paper contains identified groups of drivers, constraints, and recommendations for further successful PPP implementation in the Russian case.

Modern industry in the XXI century requires high-performance and fully automated technology. The best way to meet these requirements is the introduction of new progressive technologies in the process of transportation. One of the possible ways to increase productivity, as well as automate the process of transportation, is the transition from cyclic machines to continuous transport, namely to belt conveyors. However, with the increase in the length of the conveyor there is a need for stronger belts. This can be avoided by using intermediate drives of various designs. The article describes the principle of operation of the intermediate linear drive with transverse partitions, provides formulas for calculating the values of the tractive effort, gives comparative graphs showing the effectiveness of the use of an intermediate drive in various conditions. The possibilities of increasing the capacity of an intermediate linear drive are described.

The paper discusses the method of identifying the technical condition of induction motors by classifying the energy data coming from the main common power bus. The work shows the simulation results of induction motor operation. The correlation between occurring defects and current diagrams is presented. The developed simulation model is demonstrated. The general algorithm for conducting experiments is described. Five different experiments to develop an algorithm for the classification are conducted: determination of the motors number in operation with different power; determination of the motors number in operation with equal power; determination of the mode and load of induction electric motor; determination of the fault and its magnitude with regard to operation and load of induction motor; determination of the fault and its magnitude with regard to operation and load of induction motor with regard to non-linear load in the flow. The article also presents an algorithm for preprocessing data to solve the classification problem. In addition, the classification results are shown and recommendations for testing and using the classification algorithm on a real object are made.

This paper presents a methodology for creating a soft sensor for predicting the bearing wear of electrical machines. The technique is based on a combination of Park vector methods and a classifier based on an artificial neural network (ANN‐classifier). Experiments are carried out in la-boratory conditions on an asynchronous motor of AIR132M4 brand. For the experiment, the inner rings of the bearing are artificially degraded. The filtered and processed data obtained from the installation are passed through the ANN‐classifier. A method of providing the data into the classi-fier is shown. The result is a convergence of 99% and an accuracy of 98% on the test data.

The results of tests for resistance to abrasive wear on highly abrasive hard rock white electrocorundum are presented. The main material of fast-wearing elements of mining and processing equipment-110G13L steel (Gadfield steel) in comparison with other 9 grades of steel and cast iron, including specially developed wear-resistant foreign steels such as Hardox and Miiluks, is analyzed. The studies were carried out using an experimental stand for studying the material wearing process. On the stand the sample was fixed in a holding device and, after being brought into contact with the abrasive, it was rotated under a constant load. As a result of the experiments, it was confirmed that the order of placement of the tested materials in terms of increasing wear resistance coincides with their placement in terms of increasing hardness. At the same time, the wear resistance of the most resistant material – U8A steel after quenching – is about 4 times higher than this indicator for the least resistant components – low-carbon steel 25L, including gray and high-strength cast iron SCH21, VCH35. The wear resistance of 110G13L steel, as well as 65G, U8 steels in the hardened state, is from 1.5 to 2 times higher than that of foreign steels M400, H450, M500, H500. The results of the conducted studies allow us to evaluate the analyzed materials on the basis of their wear resistance and hardness indicators on the feasibility of using them in the manufacture of fast-wearing parts of mining equipment. Based on the research data, it seems promising to develop new ways to increase the wear resistance of domestic steel, including 110G13L steel traditionally used in mining.

Currently, the determination of the emission rate of suspended solids from a unit of the surface area of a man- made mass at various parameters of the wind flow is not sufficiently described. The analysis of the world experience of researchers shows that existing laboratory installations have various design features that do not allow to correctly determine the mass of the dust being flapped and wind-blown. Based on the analysis results, the concept of an innovative laboratory installation for the study of dust-forming surfaces has been developed. It takes into account the influence of wind shadows, the deturbulization of an artificially created air flow, the possibility of regulating not only the flow velocity mode, but also the creation of a vacuum or disturbance in the area of sample placement, as well as the formation of a certain angle of wind flow attack relative to the surface. The concept provides for the possibility of determining the volume of dust emissions by the values of the lost dust masses in the sample and by the values of dust concentrations in the outgoing stream. The calculation of the main basic elements of the installation using the ANSYS FLUENT software package was carried out. The model and configuration of the wind tunnel have been developed and calculated, the main geometric parameters and functional elements for the possibility of use in scientific work have been determined. For practical use of the empirical roughness value of the underlying surface, its values are recommended in a wide range - from zero for the water surface to 0.44 for large cities with tall buildings and skyscrapers.

Currently in the Russian Federation there is a large number of methods for determining the economic damage from environmental pollution. They make it possible to assess the quantitative damage caused by the industry to the environment and consider the environmental pollution factor when calculating the economic performance of enterprises. In general, all methods can be reduced to three main types, whose main advantages and disadvantages, as well as applicability for adjusting the performance of enterprises, and inclusion in environmental performance assessment are discussed in this article. The authors proposed a step-by-step procedure for including the factor of negative impact on the environment in the evaluation of companies’ performance. First, a preliminary consolidated assessment is made by the method of specific damage. Secondly, the economic effect is calculated by the method of generalized indirect estimates. If necessary, clarification of calculations by the method of direct calculation is carried out. When calculating production efficiency indicators, considering the nature protection activities of the enterprise, a method of accounting for the prevented damage is proposed.

This work presents results of experimental researches of influence of various hightemperature thermomechanical treatment (HTMT) modes in 35KhGSA steel – material applied in rock-destroying cutters – on hardness and wear rate for the most common abrasive rock in mining operations – sandstone. It has been found out that HTMT leads to increase of steel hardness and reduction of wear rate compared to heat treatment applied at manufacture of cutters. The maximal increase of hardness (by 23%) and reduction of wear rate (by 38%) corresponds to the mode of distortion accumulation of ∼1,5 at 900 °С at water quenching and tempering at 230 °C. A conclusion that thermomechanical treatment is an effective way to increase the wear resistance of steels applied in the conditions of abrasion wear has been drawn.

In this paper, we consider the need to create an algorithmized digital platform for the development of electric charging networks of road transport and to optimize the load on the current power grid complex. In modern conditions, this platform can become an example of a mechanism for public-private partnerships and the development of environmentally friendly transport. The purpose of the platform is to provide users with up-to-date information about the state of the electric vehicle battery, reduce the cost of creating a network charging infrastructure for electric vehicle transport, automated resource accounting for power supply companies, and other services. The use of information technologies to combine the processes of economic relations in the field of energy sales services will attract funds for infrastructure development by increasing the load factor of generating capacities and unloading power centers. In the article, the authors propose a digital platform architecture using modern technologies such as IIoT, Vehicle to Grid (V2G), Machine learning, Big Data.

Today the industry is facing a shortage of skilled workers and an aging workforce, which will eventually lead to a loss of knowledge. But augmented reality technology can connect field workers with experts who are able to provide remote guidance in real time. The subsequent advantage is that the information obtained by AR devices can be used as accumulated successful experience in the future, which facilitates decision-making in specific business processes of the company. With AR, employees gain experience and skills much faster. This paper shows the application of augmented reality technology in the maintenance of electromechanical equipment. The main functions of the augmented reality system for servicing electrical equipment are presented, the solution to the problem of integrating an augmented reality software application with existing automation systems is shown, and the methods of interaction of the developed software module with third-party modules, for example, various analytical modules, etc. are described.

Prospects of ecological technologies development in the Russian oil industry have been developed in the paper. Reducing the negative impact on the environment is inextricably linked with the development of applied technologies. On the basis of scientific, systematic and comparative analysis we have identified major environmental issues arising from extraction, processing and use of oil and the directions of their solution. The greatest negative impact on the environment is provided by such factors as sludge formation, burning of associated gas, increased accident rate and the use of fuel oil. A number of problems in the field of environmental safety in the oil industry may be avoided by using innovations. In this work, we have assessed the prospects for reducing the negative impact on the environment through the application of modern engineering solutions in the field of ecology. In order to reduce environmental impacts and economic costs, it is primarily proposed to develop technologies in the area of safe waste management, modernization of treatment facilities and prevention of oil and oil products spills.

The most important task of the production of the mineral raw materials industry is to increase the efficiency of the equipment and infrastructure in operation. In particular, this also applies to the need to create transport systems with high productivity while reducing the cost of transporting mineral raw materials and waste from its processing. Particular attention is paid to the use of hydraulic filling systems as a measure to prevent man-made tectonic earthquakes during prolonged and continuous development of deposits. In this paper, we consider the problem aimed at solving the fundamental problems of developing effective methods for controlling the flow of pasty substances in pipelines of variable cross-section, intended for the production of pumping equipment and used in such industries as mining, chemical, food, etc.

This article is devoted to the prediction of the residual life based on an estimate of the technical state of the induction motor. The proposed system allows to increase the accuracy and completeness of diagnostics by using an artificial neural network (ANN), and also identify and predict faulty states of an electrical equipment in dynamics. The results of the proposed system for estimation the technical condition are probability technical state diagrams and a quantitative evaluation of the residual life, taking into account electrical, vibrational, indirect parameters and detected defects. Based on the evaluation of the technical condition and the prediction of the residual life, a decision is made to change the control of the operating and maintenance modes of the electric motors.